JD:

EDUCATION, EXPERIENCE, & SKILLS REQUIRED 

8–11 years of experience in a software engineering role, with a focus on backend or full-stack development 

Proven track record of AI/LLM application development or integration 

Strong experience in Python-based AI application development with API engineering 

Proficiency in RESTful APIs, microservices, and cloud-based AI deployments (AWS, Kubernetes, Lambda) 

Familiarity with AI orchestration tools for AI workflow automation 

Knowledge of SQL and NoSQL databases (PostgreSQL) for AI-powered search 

Experience working in Agile teams and delivering AI-driven features in a cloud-first environment 

Bachelor’s Degree in Computer Science or related field 

Understanding of healthcare data privacy regulations (HIPAA, GDPR) is a plus 

BEHAVIORS & ABILITIES REQUIRED 

Ability to learn and adapt rapidly while producing high-quality code 

Capable of translating AI/LLM concepts into practical, scalable software solutions 

Innovative thinker who finds creative ways to execute when historical context is limited 

Strong analytical skills to assess potential designs and choose the best solution for the business 

Committed to delivering results under challenging circumstances 

Skilled at mentoring and coaching to elevate junior team members 

Able to uphold best engineering practices for quality, security, and performance 

RESPONSIBILITIES MAY INCLUDE, BUT ARE NOT LIMITED TO 

Technical Execution 

AI-Powered Software Development & API Integration 

Design, develop, and deploy AI-powered applications that enhance RCM automation 

Develop AI-driven microservices and ensure cloud-native deployment.

AI Optimization & Performance Tuning 

Optimize AI model performance via API configurations rather than custom fine-tuning 

Leverage AI orchestration tools (LangChain) to automate complex AI workflows 

Microservices & APIs 

Build and maintain RESTful APIs for AI features; integrate with internal and external systems 

Accurately estimate development tasks and own them through completion 

Deliver high-quality software components 

Ensure solutions meet reliability, performance, and compliance standards (especially for healthcare data) 

Evaluate and propose new technologies 

Identify scalable open-source frameworks or cloud-based AI services, ensuring robust and cost-effective implementations 

Code reviews & quality assurance 

Participate in peer reviews, ensuring adherence to coding conventions and best practices 

Write, debug, and deploy code to production, promptly delivering fixes 

Contributions to the Team 

Subject matter expert 

Serve as a go-to resource for AI/LLM-related application architecture and best practices 

Stay current with industry trends (agentic AI, genAI) and share insights with the broader team 

Scrum team participation 

Collaborate in Agile ceremonies: daily stand-ups, sprint planning, retrospectives 

Commit to sprint goals and deliver incremental value to customers and internal stakeholders 

Team accountability 

Encourage a culture of ownership: if you build it, you support it post-release 

Help the team continuously improve velocity, code quality, and automation

Cross-Functional Coordination & Communication

Partner with product and UX 

Translate requirements for AI-driven RCM features into technical designs, ensuring alignment with user needs 

Collaborate on user experience improvements requiring generative AI insights (e.g., claims code suggestions) 

Stakeholder engagement 

Work closely with compliance/security teams to maintain HIPAA/data governance standards 

Communicate technical roadmaps, dependencies, and timelines effectively to non-technical audiences 

Broad knowledge sharing 

Educate peers on AI/ML design patterns, cloud infrastructures, and best practices 

Build strong relationships with cross-functional teams, bridging technology and business domains